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DOE (Design of Experiments) Help: Montgomery's Industrial Engineering book

F

Fluidfont

#1
DOE stuff

Hi,

Couldn't think of anywhere else to post this but here.
I'm an Industrial Engineering major taking a class on DOE right now. We are using Montgomery's book for those of you who are familiar. Anyhow, I'm having a hard time grasping the material. It isn't clicking like SPC/SQC did for me. Can any of you professionals out there help?

Thanks
 
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D

D.Scott

#2
DOE is a pretty big topic and by using the search feature there are some good threads available here that discuss most of the more common questions.

Is there something specific you don't understand? Maybe if you describe what material you are having trouble grasping we could offer some guidance.

Dave
 

Mike S.

Happy to be Alive
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#4
Fluidfont said:
Hi,

Couldn't think of anywhere else to post this but here.
I'm an Industrial Engineering major taking a class on DOE right now. We are using Montgomery's book for those of you who are familiar. Anyhow, I'm having a hard time grasping the material. It isn't clicking like SPC/SQC did for me. Can any of you professionals out there help?

Thanks
DOE isn't the easiest thing in the world to master, especially if the instructor isn't particularly good. Let's face it, some teachers can really teach, others just know the material.

If memory serves, I think Juran's Quality Handbook has a section on DOE that might be of some help. Also, as already suggested, an internet search might be of some help.

And like Dave said, if you have a specific question, post it. I'll bet some of the DOE gurus here can help.

Stick with it! And good luck!
 
F

Fluidfont

#5
Well, my professor is pretty well known according to my friend who works at Boeing. Kailash Kapur if any of you have ever heard about him. I think it's hard for people really involved in their field to explain things in an easy matter.

One hang up I'm having with the material is with the ANOVA table. It's pretty easy for me to calculate everything I need to and make the table, but I don't quite understand this whole Sum of Squares deal. It seems a little like monkey business to me. How do I explain to someone that doing a set of mathematical algorithms is essentially paritioning the variance that exists in an experiment. I know that I could look at the mathematical proof of how it is done, but the thing I don't get is how they know that a certain set of computations will guarantee a numerical representation of the physical problem in ANOVA.

For example, if I had two apples on a table and I pulled one away, I could prove that 2 - 1 = 1. ANOVA gets crazy because there is all this squaring, adding, dividing, and subtracting of numbers. I feel like I'm being lost in the calculations even though I know how to do them.

???
 
T

Tom Slack

#6
Let's see if this helps. Since you have a handle on control charts, try this experiment:
1. Create an individual control chart 10 points with a mean of 20 and a std dev of 2. Pretend this process was at Temperature 1.

2. Create an another individual control chart 10 points with a mean of 15 and a std dev of 2. Pretend this process was at Temperature 2.

3. Calculate the average variance of the 2 control charts (should be about 4).

4. Calculate the variance of all 20 points.

5. Finally, do an F test on the results 3 and 4.

6. Think about why the variance of step 4 is greater than step 3.

OK, I know that isn't exactly the same as an ANOVA table, but it is close. Sums of Squares is kind of like variance.

The people that made up the names of these procedures weren't good at naming things. ANOVA stands for Analysis of Variance, but it purpose is to get a handle on differences in means. There is another procedure called Analysis of Means, and you guessed it, it to get a handle on differences in variances.

I hope this helps.

Tom
 
R

Rob Nix

#7
Fluidfont,

Tom provides a good example. Most measures of dispersion: variance, standard deviation, etc. use as part of their formula a sum of squares, or Root Mean Square. This is to help "level out" extreme values and makes it a better description of variability (you should have a good understanding of the central limit theorem) than range which only uses two values.

NOTE: Kal Kapur was an instructor of mine for one of the design of experiments classes I took in the mid to late 80's. He was very good at explaining the practical aspects of the methods as I recall.

As you go through this material, don't let yourself get bogged down worrying about the statistics. Use the formulas without thinking about it too much. After awhile, and after looking at many case studies, you will begin to see the logic behind the formulas. When you have mulitple variables, there are no easy ways to determine each of their contributions, not to mention their interactions.

You'll do fine.
 
F

Fluidfont

#8
Yeah, I have no problem crunching the numbers and getting what I need to.. I just like to have a feeling of competence when I'm doing it though. Man I love this forum.
 
R

Rachel

#9
Fluidfont said:
Yeah, I have no problem crunching the numbers and getting what I need to.. I just like to have a feeling of competence when I'm doing it though. Man I love this forum.

Yeah - I took DOE in my last year at Waterloo. I loved it, to be honest! I wish I could recommend a textbook, but my prof took a bit from here and a bit from there and compiled his favourite stuff to make us course notes.
 
T

Tom Slack

#10
Fluidfont said:
Yeah, I have no problem crunching the numbers and getting what I need to.. I just like to have a feeling of competence when I'm doing it though. Man I love this forum.
I feel there is an improvement in the way you feel about the material from your first post. :applause: I sense you are a hands on learner. Now would be a good time to chill out and spend the weekend at the driving range. Take a tape measure, a few different brands of drivers, a few different brands of golf balls and some friends and do a full factorial fixed effects experiment. It may not help your course, but it should improve your game! :biglaugh:

BTW, is anybody coming down for the Masters?

Tom
 
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